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12 November 2024 Spatiotemporal dynamics and center of gravity shifts in China’s cold chain logistics infrastructure
Weiwei Gong, Yuhang Wang, Langya Zhou, Cheng Chen, Lingyun Zhou
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Proceedings Volume 13395, International Conference on Optics, Electronics, and Communication Engineering (OECE 2024) ; 133953D (2024) https://doi.org/10.1117/12.3049994
Event: International Conference on Optics, Electronics, and Communication Engineering, 2024, Wuhan, China
Abstract
This study employs the LISA-SDE Hybrid Modeling Approach to analyze the distribution and dynamics of cold chain logistics enterprises across China from 2018 to 2022, focusing on enterprise numbers, storage capacities, and vehicle fleets. Results from the LISA analysis indicates strong, persistent spatial clustering in regions such as Gansu and Qinghai, with Gansu maintaining high LISA indices from 0.798 in 2018 to 0.789 in 2022 and consistently low p-values below 0.005. The Standard Deviation Ellipse analysis reveals a significant geographic center shift northward by approximately 21 kilometers between 2018 and 2019 and an increase in the spatial extent of logistics facilities, as evidenced by the expansion of the ellipse area from 228.417 square units in 2018 to 231.006 square units in 2021. These findings highlight the dynamic evolution of China’s cold chain logistics infrastructure, underscoring significant advancements in spatial distribution and strategic clustering, which are crucial for informing infrastructure development and policy-making aimed at modernizing the system by 2035.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Weiwei Gong, Yuhang Wang, Langya Zhou, Cheng Chen, and Lingyun Zhou "Spatiotemporal dynamics and center of gravity shifts in China’s cold chain logistics infrastructure", Proc. SPIE 13395, International Conference on Optics, Electronics, and Communication Engineering (OECE 2024) , 133953D (12 November 2024); https://doi.org/10.1117/12.3049994
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KEYWORDS
Nanoimprint lithography
Data storage
Statistical analysis
Industry
Modeling
Matrices
Sustainability
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